1455 Open source projects that are alternatives of or similar to Attention Mechanisms

A curated list of recent models of text generation and application

TextGAN is a PyTorch framework for Generative Adversarial Networks (GANs) based text generation models.

Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application.

Materials for deep NLP course

Tracking the progress in non-autoregressive generation (translation, transcription, etc.)

a sklearn wrapper for Google's BERT model

基于自然语言理解与机器学习的聊天机器人，支持多用户并发及自定义多轮对话

Compendium of the resources available from top NLP conferences.

This Word Does Not Exist

The codes of paper "Long Text Generation via Adversarial Training with Leaked Information" on AAAI 2018. Text generation using GAN and Hierarchical Reinforcement Learning.

My Reading Lists of Deep Learning and Natural Language Processing

🏇 聊天机器人，自然语言理解，语义理解

Keras Implementation of Aspect based Sentiment Analysis

Self-contained Machine Learning and Natural Language Processing library in Go

Cornell Instruction Following Framework

DGMs for NLP. A roadmap.

Lyrics Generator aka Character-level Language Modeling with Multi-layer LSTM Recurrent Neural Network

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

💫 Automated codification of Greek Legislation with NLP

Programming assignments from all courses in the Coursera Natural Language Processing Specialization offered by deeplearning.ai.

Source code and data for the paper "Towards String-to-Tree Neural Machine Translation"

GPT-2 French demo | Démo française de GPT-2

A Natural Language Toolkit for Indian Languages

Python tutorials as Jupyter Notebooks for NLP, ML, AI

Data-centric declarative deep learning framework

Electra pre-trained model using Vietnamese corpus

Automatic Generation of Brief Summaries of Time-Series Data

PyTorch Implementation of OpenAI GPT-2

ByteNet for character-level language modelling

This repository contains PyTorch implementation for the baseline models from the paper Utterance-level Dialogue Understanding: An Empirical Study

A list of NLP(Natural Language Processing) tutorials

Baidu's open-source Sentiment Analysis System.

Pre-Trained Models for ToD-BERT

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

Mapping a variable-length sentence to a fixed-length vector using BERT model

使用 RASA NLU 来构建中文自然语言理解系统（NLU）| Use RASA NLU to build a Chinese Natural Language Understanding System (NLU)

Aspect Based Sentiment Analysis, PyTorch Implementations. 基于方面的情感分析，使用PyTorch实现。

An overview of the AI-as-a-service landscape

Ruby SDK for Dialogflow

Neural Models for Conversational AI

XLNet Extension in TensorFlow

NLP and Text Generation Experiments in TensorFlow 2.x / 1.x

package lingo provides the data structures and algorithms required for natural language processing

Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019

Multi-Task Deep Neural Networks for Natural Language Understanding

🔥 Korean GPT-2, KoGPT2 FineTuning cased. 한국어 가사 데이터 학습 🔥

A curated list of NLP resources for Hungarian

A two-level morphological analyzer for Turkish.

How to build RNNs and LSTMs from scratch with NumPy.

A bidirectional LSTM with attention for multiclass/multilabel text classification.

Fast and customizable text tokenization library with BPE and SentencePiece support

Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)

DialoGLUE: A Natural Language Understanding Benchmark for Task-Oriented Dialogue

Important paper implementations for Question Answering using PyTorch

SLING - A natural language frame semantics parser

NLP made easy

Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera